蚁群算法在检验规划中的应用

2009 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Pub Date : 2009-05-11 DOI:10.1109/CIMSA.2009.5069921

R. Schmitt, Hanqing Zheng, Xiongfei Zhao, Niels Konig, Raphael Rocha Coelho

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引用次数: 7

摘要

本文介绍了蚁群优化算法在检验规划中的应用。由于检验计划是一项耗时的任务，优化这些活动在质量检验领域起着重要作用。本文分别给出了旅行商问题(TSP)和子集问题的局部检测路径规划(LIPP)和测量设备选择(MDS)的提取方法。提出了一种基于最大最小蚂蚁系统(MMAS)的蚁群算法。在工业工件上的实验证明了蚁群算法在检验规划中的适用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Application of ant colony optimization to inspection planning

Within this paper the application of an ant colony optimization (ACO) algorithm to inspection planning is presented. Since inspection planning is a time consuming task, optimizing these activities plays a major role in the quality inspection field. In this paper the extraction procedures of local inspection path planning (LIPP) and measurement device selection (MDS) to travelling salesman problem (TSP) and subset problem are presented respectively. An ACO algorithm based on Max-Min Ant System (MMAS) is presented for solving the problems. Experiment on industrial workpiece shows the applicability of ACO to inspection planning.

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来源期刊

2009 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications

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